Home AI Courses Google Cloud Certification: Cloud Data Engineer Professional Certificate

Google Cloud Certification: Cloud Data Engineer Professional Certificate

(0 reviews)

Investigate the objectives and advantages of Google's Big Data and Machine Learning products, including the use of BigQuery for interactive analysis, Cloud SQL, and Dataproc for migrating MySQL and Hadoop applications, and the selection of a variety of data processing tools on Google Cloud.

Key AI Functions:Tensorflow,Bigquery,Information Engineering,Google Cloud,Cloud Computing

Description

Reviews

Alternative Tools

Description for Google Cloud Certification: Cloud Data Engineer Professional Certificate

Determine the objectives and advantages of the primary Big Data and Machine Learning products in Google Cloud.

Utilize BigQuery to conduct interactive data analysis.

Utilize Cloud SQL and Dataproc to transfer existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.

Select from a variety of data processing products available on Google Cloud.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 1

Offered by: On Coursera provided by Google Cloud

Duration: 1 month at 10 hours a week

Schedule: Flexible

Reviews for Google Cloud Certification: Cloud Data Engineer Professional Certificate

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Featured Tools

ML in Mathematics: PCA

Authoritative GCP

Exploring AI Possibilities

Product Management: Capstone Project

Gen AI in Marketing Specialization

Alternative Tools for Google Cloud Certification: Cloud Data Engineer Professional Certificate

Gen AI Supporting Data Engineers

Begin your vocation in generative AI data engineering. Obtain the necessary skills to secure a position as a data engineer by acquiring an understanding of generative AI. No prior experience is required.

#Convolutional Neural Network #Information Engineering

Intro to Gen AI Learning Path

This learning path provides a thorough overview of generative AI. This specialization delves into the ethical considerations that are essential for the responsible development and deployment of AI, as well as the foundations of large language models (LLMs) and their diverse applications.

#Generative AI #Large Language Models

ML on Google Cloud

Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world

#Tensorflow #Machine Learning

Gemini in Gmail

Learn how to use Gemini for Google Workspace to boost productivity and efficiency in Gmail through its generative AI features.

#AI Assitant #Gemini

GenAI and LLMs on AWS

Learn to build machine learning solutions using Generative AI on AWS, including an understanding of AWS cloud computing and utilizing services like Amazon Bedrock.

#AWS #Cloud Computing

Rust Programming Specialization

Acquire the skills necessary to program powerful systems in Rust. Through projects in data engineering, Linux tools, DevOps, LLMs, Cloud Computing, and machine learning operations, acquire the skills necessary to develop software that is both efficient and robust, utilizing Rust's distinctive safety and speed.

#Computer Programming #Rust (Programming Language)

Deep Learning Specialization

Become an adept in the field of machine learning. Break into the field of artificial intelligence by mastering the fundamentals of deep learning. Recently upgraded with state-of-the-art methodologies!

#Recurrent Neural Network #Tensorflow

Google Cloud Certification: ML Engineer

Gain the skills needed for a machine learning engineering role and prepare for the Google Cloud Professional Machine Learning Engineer certification exam by learning to design, build, and productize ML models using Google Cloud technologies.

#Tensorflow #Bigquery

Advanced ML on Google Cloud Specialization

Gain practical experience in optimizing, deploying, and scaling machine learning models using Google Cloud Platform through a structured five-course specialization with hands-on labs and a focus on advanced topics and recommendation systems.

#Tensorflow #Convolutional Neural Network